A Pythagorean fuzzy number-based integration of AHP and WASPAS methods for refugee camp location selection problem: a real case study for Istanbul, Turkey

Ayyildiz E., Erdogan M., Gumus A. T.

NEURAL COMPUTING & APPLICATIONS, cilt.33, sa.22, ss.15751-15768, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 33 Sayı: 22
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1007/s00521-021-06195-0
  • Dergi Adı: NEURAL COMPUTING & APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Biotechnology Research Abstracts, Compendex, Computer & Applied Sciences, Index Islamicus, INSPEC, zbMATH
  • Sayfa Sayıları: ss.15751-15768
  • Anahtar Kelimeler: Location selection, Multi-criteria decision making, Pythagorean fuzzy sets, Refugee camp, OCCUPATIONAL-HEALTH, RISK-ASSESSMENT, SAFETY, MODEL, EXTENSION
  • Karadeniz Teknik Üniversitesi Adresli: Hayır

Özet

There is an increase in the number of people who have changed their country for compulsory reasons due to the wars experienced worldwide. This raises the problem of identifying the regions where these people, called refugees, will live in the countries. In this regard, we determine in this paper where the camps established for refugees living in Istanbul should be located. The presence of many quantitative and qualitative factors which should be handled in determining the best location has enabled this problem to have multi-criteria decision-making structure. In addition, the advantage of fuzzy logic is used to convert the evaluations taken from experts into available numbers and to include them in decision-making process. For this purpose, a novel model with the integration of Pythagorean fuzzy AHP and Pythagorean fuzzy WASPAS methods is proposed for the first time in the literature, to select the best location for the refugee camp. In addition, a comparative analysis is applied to determine the validity of the results obtained and the sensitivity analysis is applied to check the robustness of the model. As a result, the most suitable location for a refugee camp in Istanbul is identified reasonably with the proposed model.